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Across

1. A type of machine learning that involves training a system through trial-and-error using feedback from its environment.

2. AI systems can be vulnerable to hacking and manipulation, leading to potential security breaches and misuse of information.

3. AI systems are limited to what they have been trained on and cannot generate truly original ideas or concepts.

4. A type of artificial intelligence that attempts to simulate human thought processes and decision-making.

5. Machine learning software that acts autonomously on a user's behalf.

6. Using historical data and machine learning algorithms to make predictions about future events or outcomes.

7. Explainability is the ability to provide understandable explanations or justifications for the decisions and outcomes generated by an AI system.

8. AI systems collect and process vast amounts of personal data, raising concerns about privacy and data protection.

9. Machine learning models that can generate new and original content, such as images, texts, or music.

10. The process of interpreting the meaning of words and phrases in context.

Down

11. A type of machine learning algorithm modeled after the structure of the human brain, capable of learning complex patterns and relationships.

12. A type of machine learning algorithm that uses principles of evolution to generate solutions to complex problems.

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